Case Studies



Asian Paints, 09 Solutions


Crafting ML enabled tools for faster sales cycles

How might we leverage real-time data to maintain a healthy relationship between all stakeholders in the sales-supply chain?


It is evident that machine learning enabled cycles can create seamless connects between the data from the field and deliver it to strategic teams. The interpretation and adoption of insights however remain a key challenge. This is what we worked on.

With ample platforms available today that capture real-time data, we needed to make the data more relevant for each user. We crafted Milo, an information & communication tool that leverages real-time data to maintain a healthy relationship between all stakeholders in the sales-supply chain.


Milo was deployed as a front-end on o9's Mpower platform to breakdown realtime updates into usable information formats. It was designed to be customisable to each user’s unique needs and delivered a system that made information ambient-to-actionable.

For the system to work, we needed to leverage the 2-3 min interaction between the salesman and the dealer. It was essential that this technological intervention would not hamper this relationship of face-to-face communication. An adaptive system had to be developed for a comfortable adoption.


The system crafted worked towards behaviourally shifting a perspective on the amount of information needed and consumed. It was essential that raw data was available for deep-dive as and when needed, however, information layout could be based on learning the patterns of consumption during days, weeks and months. Basis this, a modular UI was created that could change from action based nuggets to analysed data with charts, to itemised raw data. The UI was based on android guidelines for ease of development and to reduce threshold to try new layouts. This system was deployed for Asian Paints' sales and strategy teams pan India.